The Dutch Early-Stage Melanoma (D-ESMEL) study: a discovery set and validation cohort to predict the absolute risk of distant metastases in stage I/II cutaneous melanoma.

Early-stage cutaneous melanoma patients generally have a favorable prognosis, yet a significant proportion of metastatic melanoma cases arise from this group, highlighting the need for improved risk stratification using novel prognostic biomarkers. The Dutch Early-Stage Melanoma (D-ESMEL) study introduces a robust, population-based methodology to develop an absolute risk prediction model for stage I/II melanoma, incorporating clinical, imaging, and multi-omics data to identify patients at increased risk for distant metastases. Utilizing the Netherlands Cancer Registry and Dutch Nationwide Pathology Databank, we collected primary tumor samples from early-stage melanoma patients, with and without distant metastases during follow-up.

Exploring Motives Behind Ideal Melanoma Survivorship Care Plans With Multiple Stakeholders: A Cocreation Study.

Background: Survivorship care plans (SCPs), ie, personalized health care plans for cancer survivors, can be used to support the growing group of melanoma survivors throughout their disease trajectory. However, implementation and effectiveness of SCPs are suboptimal and could benefit from the involvement of stakeholders in developing a user-centered design.

Objective: The aim of this study was to identify the ideal SCP for patients with melanoma in terms of functions and features to be included according to different stakeholders and to explore their underlying motives.

Embedding artificial intelligence in healthcare: An ethnographic exploration of an AI-based mHealth app through the lens of legitimacy.

Purpose: Skin cancer, a significant global health problem, imposes financial and workload burdens on the Dutch healthcare system. Artificial intelligence (AI) for diagnostic augmentation has gained momentum in dermatology, but despite significant research on adoption, acceptance, and implementation, we lack a holistic understanding of why technologies (do not) become embedded in the healthcare system. This study utilizes the concept of legitimacy, omnipresent but underexplored in health technology studies, to examine assumptions guiding the integration of an AI mHealth app for skin lesion cancer risk assessment in the Dutch healthcare system.